Gaurav Verma

Computer Science Ph.D. student at Georgia Tech | Interested in Multimodal Learning, Natural Language Processing, and Computational Social Science

Email: gverma@gatech.edu



[ curriculum vitae (pdf) ]


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I am a second-year Ph.D. student in Computer Science at Georgia Tech, where I am advised by Prof. Srijan Kumar. I am interested in developing robust and trustworthy machine learning methods that can fuse information from different modalities to solve problems that impact the well-being of individuals and society. My specific interests include: learning from multimodal data, machine learning robustness, natural language processing, and computational social science. [CV]

Previously, I was a research intern at Adobe Research (Summer 2022) where I was mentored by Prof. Ani Nenkova and Dr. Ryan A. Rossi. I worked on understanding cross-modal (image-text) interactions in documents.

I completed my undergraduate studies at the Indian Institute of Technology Kanpur. At IIT Kanpur, I worked with Prof. Tanaya Guha on learning modality-independent representations for affective analysis and retrieval of multimedia. Before starting my doctoral studies at Georgia Tech, I was at Adobe Research (India), where I worked on a wide range of research projects, like stylistic analysis and generation, multimodal content synthesis (TechCrunch), and search query construction. Please see the Publications page for more details on published papers and patents.

Apart from research, I love to spend most of my time reading books (📚). I also have some affinity for sports – basketball (🏀) and table tennis (🏓). The quickest way to get in touch would be through email (📧). I am also somewhat active on Twitter. More details are available in the Contact section.

Recent Awards:
• College of Computing Rising Star Doctoral Student Research Award (2022)
• Adobe Research Ph.D. Fellowship Finalist (2022)
• Best Paper Runner-up Award at WISE 2021
• AAAI ICWSM-2021 Best Reviewer Award

Academic Service: Program Committee Member/Reviewer for:
Conferences: AAAI 2023, TheWebConf (WWW) 2022, ACL Rolling Review, EMNLP 2021, ACL-IJCNLP 2021, ICWSM 2021 (💐 Best Reviewer Award), ICWSM 2022, ACII 2021, CODS-COMAD 2022, and ECIR 2020.
Journal: Data Mining and Knowledge Discovery


Recent Updates

Aug, 2022 | Wrapped up my research internship with Prof. Ani Nenkova and Dr. Ryan A. Rossi at Adobe Research. I had a wonderful time working on understanding image-text interactions!
July, 2022 | Work led by Yunhao Yuan @ Aalto University has been accepted to ICWSM 2023. We study the impact of the pandemic on online LGBTQ+ communities. [pdf]
May, 2022 | Our work on examining the causal relationship between sharing misinformation and experiencing exacerbated anxiety is out in Scientific Reports. Check out the paper here: https://www.nature.com/articles/s41598-022-11488-y.
Mar, 2022 | Our work on using multimodal learning to overcome the language disparity in online content classification has been accepted to ICWSM 2022 🎉 ! [webpage] [pdf]
Jan, 2022 | Happy to share that our work on online ban evasion has been accepted to The Web Conference 2022 🎉 ! [pdf] [dataset]
Oct, 2021 | My collaborators from Adobe Research and I received the Best Paper Runner-up Award 💐 at WISE 2021 for our work on detecting document versions [pdf, image]
June, 2021 | I was one of the winners of ICWSM-2021 Best Reviewer Award 💐
Dec, 2020 | Our work on consuming linear media (like videos) in a non-linear fashion using multimodal fragments has been accepted at IUI 2021! [pdf] [video]
Sep, 2020 | EMNLP 2020: Check out our Findings paper on using reinforcement learning for generating stylized text [arXiv] and our system description for Task 2 at W-NUT [arXiv].
July, 2020 | TechCrunch talks about #ProjectSnippets in their blog! Read it here. This tool is based on our IUI'20 paper on Generating Need Adapted Multimodal Fragments [pdf].
June, 2020 | We participated in ICWSM'20 Safety Data Challenge. Here's our paper.
Mar, 2020 | Check out our work on generating multimodal fragments being presented at this year's Adobe Summit: YouTube video! Here's what the community thinks about #ProjectSnippets! [News]
Feb, 2020 | Our exploration on estimating the causal impact of stylistic attributes on a targeted goal has been accepted at WWW 2020 as a poster! Here's the paper.
Dec, 2019 | Our work on "Generating Need-Adapted Multimodal Fragments" has been accepted at IUI 2020! Check out the paper.
Dec, 2019 | Our work on "Using Image Captions and Multitask Learning for Recommending Query Reformulations" has been accepted at ECIR 2020. Here's the paper on arXiv.
Nov, 2019 | Our work on "Adapting Language Models for Non-Parallel Author-Stylized Rewriting" has been accepted as a full paper at AAAI 2020. Here's the paper on arXiv.
Aug, 2019 | Adobe asked me a few questions on completing one year at Adobe Research [AdobeLife]
Mar, 2019 | Work on command recommendation accepted at UMAP 2019 [project page]
Feb, 2019 | Work on multimodal affective correspondence accepted at ICASSP 2019 [page]